Biometric systems such as iris recognition systems may capture an image of a feature of a person having unique characteristics (e.g., an iris) for various purposes, for example, to confirm the identity of the person based on the captured image. In the example of iris recognition, an original high-quality image of the iris of a person may be captured by an optical system and converted into an iris code which is stored in a database of iris codes associated with a group of people. In order to later confirm the identity of a user, an image of the user's iris is captured, an iris code is generated, and the iris code for the captured iris image is compared to iris codes stored in the database. If the iris code of the captured iris image exhibits a significant level of similarity with a stored iris code (e.g., the Hamming distance between the captured and stored image is less than a threshold), it can be assumed that the iris of the user is a match with the identity associated with the stored iris code.
Iris recognition systems may have difficulty capturing iris images of a sufficient quality for use in this matching procedure. For example, if a person is moving it may be difficult to capture a high-quality image of the iris. Even if a person is stationary, many optical systems require precise positioning of the iris relative to the optical system as a result of the limited depth of field or focus of the optical system.
An extended depth-of-field (EDOF) (also known as extended depth-of-focus) optical system may permit more flexibility in capturing a desired image, since the optical system can capture images having a relatively high quality over a larger distance from the optical system, with some sacrifice in the modulation transfer function (MTF) of the captured image. EDOF optical systems may include complicated optical systems, for example, including either more than one lens element or a non-circularly symmetric wavefront coding plate arranged in the entrance pupil to impart a complex wavefront shape.
EDOF optical systems used in biometrics such as iris recognition may digitally enhance captured raw images to compensate for the reduced MTF of images captured with the EDOF optical system. This additional layer of processing may consume a large amount of consuming resources, take an extended period of time, or both. This may result in excessive costs for a biometrics system utilizing EDOF technology, or may compromise the performance of biometrics systems which need to quickly process and compare biometric features with stored images (e.g., compare an iris code from a captured image iris image with a database of stored iris codes).
The above-described deficiencies of today's biometric solutions are merely intended to provide an overview of some of the problems of conventional systems, and are not intended to be exhaustive. Other problems with conventional systems and corresponding benefits of the various non-limiting embodiments described herein may become further apparent upon review of the following description.